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==2004==
* {{cite journal |author=Nikolaos Th. Korfiatis; Marios Poulos and George Bokos|title=Evaluating authoritative sources using social networks: an insight from Wikipedia|publisher=OIR|date=March 2006|year=|month=|volume=30|issue=3|page=252|pages=11}}

==2006==

===Harvard Business School, dicembre 2006===
 KARIM R. LAKHANI, ANDREW P. MCAFEE, Case study della Harvard Business School, dicembre 2006.
:Sembra da approfondire! --[[User:Christian|Christian]] ([[User talk:Christian|discussione]]) 12:15, 24 mar 2009 (CET)

==2007==
===HP Laboratories, febbraio 2007===
 [http://arxiv.org/abs/cs.DL/0702140 Assessing the Value of Coooperation in Wikipedia], HP Laboratories, Palo Alto, febbraio 2007. 
:Analisi statistica del modello wiki: il modello di Wikipedia funziona. Più modifiche subisce una voce, più è facile che ne subisca, più infine migliorerà in obiettività ed accuratezza. Articolo molto tecnico che però da una prima quantitativa prova dell'efficenza del metodo wiki. --[[User:Andrea|Andrea]] ([[User talk:Andrea|discussione]]) 01:58, 16 feb 2009 (CET)

==2008==
* {{cite journal |author=Zhang, Congle; Xue, Gui-Rong; Yu, Yong|title=Knowledge Supervised Text Classification with No Labeled Documents|publisher=PRICAI 2008: TRENDS IN ARTIFICIAL INTELLIGENCE|date=DEC 15-19, 2008|year=2008|month=0|volume=5351|issue=0|page=509|pages=12}}
:In traditional text classification approaches, the semantic meanings of the classes are described by the labeled documents. Since labeling documents is often time consuming and expensive, it; is a promising idea that asking users to provide some keywords to depict the classes, instead of labeling any documents. However, short pieces of keywords may not contain enough information and therefore may lead to unreliable classifier. Fortunately, there are large amount of public data easily available in web directories, such as ODP, Wikipedia, etc. We are interested in exploring the enormous crowd intelligence contained in such public data to enhance text classification. In this paper, we propose a novel text; classification framework called "Knowledge Supervised Learning" (KSL), which utilizes the knowledge in keywords and the crowd intelligence to learn the classifier without any labeled documents. We design a two-stage risk minimization (TSRM) approach for the KSL problem. It can optimize the expected prediction risk and build the high quality classifier. Empirical results verify our claim: our algorithm can achieve above 0.9 on Micro-F1 on average, which is much better than baselines and even comparable against SVM classifier supervised by labeled documents.
* {{cite journal |author=Kuribara, Shusuke; Abbas, Safia; Sawamura, Hajime|title=Applying the Logic of Multiple-Valued Argumentation to Social Web: SNS and Wikipedia|publisher=INTELLIGENT AGENTS AND MULTI-AGENT SYSTEMS, PROCEEDINGS|date=DEC 15-16, 2008|year=2008|month=0|volume=5357|issue=0|page=251|pages=8}}
:The Logic of Multiple-Valued Argumentation (LMA) is an argumentation framework that allows for argument-based reasoning about uncertain issues under uncertain knowledge. In this paper, we describe its applications to Social Web: SNS and Wikipedia. They are said to be the most influential social Web applications to the present and future information society. For SNS, we present an agent that judges the registration approval for Mymixi in mixi in terms of LMA. For Wikipedia, we focus on the deletion problem of Wikipedia and present agents that argue about the issue on whether contributed articles should be deleted or not, analyzing arguments proposed for deletion in terms of LMA. These attempts reveal that LMA can deal with not only potential applications but also practical ones such as extensive and contemporary applications.
* {{cite journal |author=Bruckman, Amy|title=Social Support for Creativity and Learning Online|publisher=DIGITEL 2008: SECOND IEEE INTERNATIONAL CONFERENCE ON DIGITAL GAME AND INTELLIGENT TOY ENHANCED LEARNING, PROCEEDINGS|date=NOV 17-19, 2008|year=2008|month=0|volume=0|issue=0|page=3|pages=5}}
:In the mid 1990s, we began to ask some hopeful questions about the potential of the Internet to empower the individual: Can users become creators of content, rather than merely recipients? What can people learn through working on personally meaningful projects and sharing them online? If content creation is to some degree democratized, does this have broader cultural or political implications? This enthusiasm faded a bit by the dot-com bust, and many began to wonder: will it be business-as-usual after all? But then it started happening. On Wikipedia, thousands of volunteers collaborate to create a shared resource that, while not without flaws, is astonishing in its breadth and speed of adaptation. Furthermore, the process of writing this resource is truly collaborative to a degree that should make an), Computer-Supported Cooperative Work (CSCW) professional envious. On sites like deviantART and Newgrounds, people collaborate on original art projects and animations. On MySpace, teens create their own web pages, sharing snippets of html and expressing themselves in a quintessentially teenage fashion. Blogs written by ordinary citizens have become influential in politics and culture, almost just as envisioned by science fiction writer Orson Scott Card. Peer production of content, it seems, has arrived. What has made this explosion of creativity possible is not better tools for production (though those help), but rather social contexts for sharing those products with others. The easy availability of an audience motivates people to create. In this paper, I'll review the history of peer production of content on the Internet, and present current research in the Electronic Learning Communities (ELC) Lab at Georgia Tech that aims to help support this phenomenon. Drawing on work in the fields of online community design, CSCW, and computer-supported cooperative learning, I'll discuss how we can design Internet-based environments conducive to creativity, collaboration, and learning.
* {{cite journal |author=Ortega, Felipe; Gonzalez-Barahona, Jesus M.; Robles, Gregorio|title=Quantitative Analysis of the Top Ten Wikipedias|publisher=SOFTWARE AND DATA TECHNOLOGIES|date=JUL 22-25, 2007|year=2008|month=0|volume=22|issue=0|page=257|pages=12}}
:In a few years, Wikipedia has become one of the information systems with more public of the Internet. Based oil a relatively simple architecture it has proven to be capable of supporting the largest and more diverse community of collaborative authorship worldwide. Using a quantitative methodology, (analyzing public Wikipedia databases), we describe the main characteristics of the 10 largest language editions. and the authors that work in them. The methodology is generic enough to be used oil the rest of the editions, providing a convenient framework to develop a complete quantitative analysis of the Wikipedia. Among other parameters, we study the evolution of the number of contributions and articles, their size, and the differences in contributions by different authors, inferring some relationships between contribution patterns and content. These relationships reflect (and in part, explain) the evolution of the different language editions so far, as well its their future trends.
* {{cite journal |author=Suchanek, Fabian M.; Kasneci, Gjergji; Weikum, Gerhard|title=YAGO: A Large Ontology from Wikipedia and WordNet|publisher=JOURNAL OF WEB SEMANTICS|date=MAY 08-12, 2007|year=2008|month=SEP|volume=6|issue=3|page=203|pages=15}}
:This article presents YAGO, a large ontology with high coverage and precision. YAGO has been automatically derived from Wikipedia and WordNet. It comprises entities and relations, and currently contains more than 1.7 million entities and 15 million facts. These include the taxonomic Is-A hierarchy as well as semantic relations between entities. The facts for YAGO have been extracted from the category system and the infoboxes of Wikipedia and have been combined with taxonomic relations from WordNet. Type checking techniques help us keep YAGO's precision at 95%-as proven by an extensive evaluation study. YAGO is based on a clean logical model with a decidable consistency. Furthermore, it allows representing n-ary relations in a natural way while maintaining compatibility with RDFS. A powerful query model facilitates access to YAGO's data. (c) 2008 Published by Elsevier B.V.
* {{cite journal |author=Maureen; Sun, Aixin; Lim, Ee-Peng; Datta, Anwitaman; Chang, Kuiyu|title=On Visualizing Heterogeneous Semantic Networks from Multiple Data Sources|publisher=DIGITAL LIBRARIES: UNIVERSAL AND UBIQUITOUS ACCESS TO INFORMATION, PROCEEDINGS|date=DEC 02-05, 2008|year=2008|month=0|volume=5362|issue=0|page=266|pages=10}}
:networks obtained from multiple data sources. A semantic network comprising a set of entities and relationships is often used for representing knowledge derived from textual data or database records. Although the semantic networks created for the same domain at different data sources may cover a similar set of entities, these networks could also be very different because of naming conventions, coverage, view points, and other reasons. Since digital libraries often contain data from multiple sources, we propose a visualization tool to integrate and analyze the differences among multiple social networks. Through a case study on two terrorism-related semantic networks derived from Wikipedia and Terrorism Knowledge Base (TKB) respectively, the effectiveness of our proposed visualization tool is demonstrated.
* {{cite journal |author=Haruechaiyasak, Choochart; Damrongrat, Chaianun|title=Article Recommendation Based on a Topic Model for Wikipedia Selection for Schools|publisher=DIGITAL LIBRARIES: UNIVERSAL AND UBIQUITOUS ACCESS TO INFORMATION, PROCEEDINGS|date=DEC 02-05, 2008|year=2008|month=0|volume=5362|issue=0|page=339|pages=4}}
:The 2007 Wikipedia Selection for Schools is a collection of 4,625 selected articles from Wikipedia as educational for children. Users can currently access articles within the collection via two different methods: (1) by browsing on either a subject index or a title index sorted alphabetically, and (2) by following hyperlinks embedded within article pages. These two retrieval methods are considered static and subjected to human editors. In this paper, we apply the Latent Dirichlet Allocation (LDA) algorithm to generate. a topic model front articles in the collection. Each article can be. expressed by a probability distribution on the topic model. We can recommend related articles by calculating the similarity measures among the articles' topic distribution profiles. Our initial experimental results showed that the proposed approach could generate many highly relevant articles, some of which are not covered by the hyperlinks in a given article.
* {{cite journal |author=Fukuhara, Tomohiro; Kimura, Akifumi; Arai, Yoshiaki; Yoshinaka, Takayuki; Masuda, Hidetaka; Utsuro, Takehito; Nakagawa, Hiroshi|title=KANSHIN: A Cross-lingual Concern Analysis System using Multilingual Blog Articles|publisher=2008 INTERNATIONAL WORKSHOP ON INFORMATION-EXPLOSION AND NEXT GENERATION SEARCH : INGS 2008, PROCEEDINGS|date=APR 26-27, 2008|year=2008|month=0|volume=0|issue=0|page=83|pages=8}}
:An architecture of cross-lingual concern analysis (CLCA) using multilingual blog articles, and its prototype system are described. As various people who are living in various countries use the Web, cross-lingual information retrieval (CLIR) plays an important role in the next generation search. In this paper, we propose a CLCA as one of CLIR applications for facilitating users to find concerns of people across languages. We propose a layer architecture of CLCA, and its prototype system called KANSHIN. The system collects Japanese, Chinese, Korean, and English, blog articles, and analyzes concerns across languages. Users can find concerns from several viewpoints such as temporal, geographical, and a network of blog sites. The system also facilitates users to browse multilingual keywords using Wikipedia, and the system facilitates users to find spans blogs. An overview of the CLCA architecture and the system are described.
* {{cite journal |author=Hansen, Sean; Berente, Nicholas; Lyytinen, Kalle|title=Wikipedia, Critical Social Theory, and the Possibility of Rational Discourse|publisher=INFORMATION SOCIETY|date=0|year=2009|month=0|volume=25|issue=1|page=38|pages=22}}
:Information systems researchers that apply critical social perspectives frequently emphasize the potential for information technology to serve as a mechanism for increased rationalization, domination, and control. Such theorists often overlook or discount the liberating aspects of information systems. In this study, we apply the ideal of rational discourse developed by Jurgen Habermas to the phenomenon of Wikipedia in an effort to explore empirically the emancipatory potential of information systems. We contend that Wikipedia embodies an approximation of the necessary conditions for rational discourse. While several challenges persist, the example of Wikipedia illustrates the positive potential of information systems in supporting the emergence of more emancipatory forms of communication. The corresponding implications for researchers and design professionals alike are discussed.
* {{cite journal |author=Yu, Yang; Lin, Zhangxi; Li, Qing; Xia, Guoping|title=REFINING HIERARCHIES OF PUBLIC KNOWLEDGE SPHERES BY MUTUAL AWARENESS OF KEYWORDS - TOWARDS A MORE VERSATILE WIKIPEDIA|publisher=PROCEEDINGS OF THE 38TH INTERNATIONAL CONFERENCE ON COMPUTERS AND INDUSTRIAL ENGINEERING, VOLS 1-3|date=OCT 31-NOV 02, 2008|year=2008|month=0|volume=0|issue=0|page=510|pages=8}}
:Wikipedia is the most. complete encyclopedia in the world in the history (http://en.wikipedia.org/wiki/) with 2,210,000 articles and more than 100 million links among them. Web mining of the spheres of knowledge in wikipedia will help us to discover the anatomy of the Public knowledge structure and understand how the knowledge is accumulated and refined with the well conceived incentive mechanism. Current wikipedia spheres form with regard to mutual referencing among keywords. The structure of the link hierarchies is not optimized because these hierarchies were manually built and conceived with simple keyword matching. This paper focuses on improving the efficiency of knowledge retrieval from the wikipedia spheres with more accurate links among them. It defines a new measure of distance in terms of mutual awareness of keywords, which is underpinned by computational models. In this way, we can use the measure of mutual awareness to rank and reorient the keywords to discover the closest keyword clusters. This can significantly increase the accuracy of knowledge retrieval in wikipedia. We have collected more than 99% of keywords and their links from wikipedia.org. The application of hierarchical clustering resulted in important findings
* {{cite journal |author=Royal, Cindy; Kapila, Deepina|title=What's on Wikipedia, and What's Not ... ? Assessing Completeness of Information|publisher=SOCIAL SCIENCE COMPUTER REVIEW|date=0|year=2009|month=FEB|volume=27|issue=1|page=138|pages=11}}
:The World Wide Web continues to grow closer to achieving the vision of becoming the repository of all human knowledge, as features and applications that support user-generated content become more prevalent. Wikipedia is fast becoming an important resource for news and information. It is an online information source that is increasingly used as the first, and sometimes only, stop for online encyclopedic information. Using a method employed by Tankard and Royal to judge completeness of Web content, completeness of information on Wikipedia is assessed. Some topics are covered more comprehensively than others, and the predictors of these biases include recency, importance, population, and financial wealth. Wikipedia is more a socially produced document than a value-free information source. It reflects the viewpoints, interests, and emphases of the people who use it.
* {{cite journal |author=Luyt, Brendan; Zainal, Chia Zuhaila Bte Chia; Mayo, Olivia Victoria Petines; Yun, Tan Siow|title=Young people's perceptions and usage of Wikipedia|publisher=INFORMATION RESEARCH-AN INTERNATIONAL ELECTRONIC JOURNAL|date=0|year=2008|month=DEC|volume=13|issue=4|page=0|pages=1}}
:Introduction. This exploratory study investigated the perception and usage of Wikipedia among young people. Method. Fifteen respondents aged thirteen to twenty-four were selected for the study. The respondents were composed of secondary and tertiary students, and recent tertiary level graduates. An interview schedule was designed to explore user experiences at three levels: the initial encounter with Wikipedia, the time when the user felt comfortable with Wikipedia, and the user's current state. Questions were open-ended and semi-structured to allow for probing. Interviews were conducted over a span of two weeks with each interview lasting 30-45 minutes. Follow-up questions were asked of some of the respondents for clarification purposes. Analysis. Interview data was used to test Wikipedia, viewed as a technology, against the model of technological appropriation developed by Carroll et al. for their own study of mobile phone use among young people. Results. We found that although Wikipedia is initially attractive for young people, it generally fails to become deeply integrated (appropriated) into the everyday lives of users, instead remaining an instrumental tool for the fulfilment of a narrow range of tasks. We also found that over time respondents do become aware of the problems of accuracy that Wikipedia poses. Conclusions. Given that Wikipedia has not assumed the role of a key technology in the lives of the young people studied here, concern over its use by educators may be overstated. Also, the fact that the respondents were aware of the drawbacks to its use should make the message of the need for checking alternative sources an easier one to impart to students. The key conclusion, however, is the need for those wishing to design more popular information systems to take into account the deeper needs of users to experiment with technology in order to make it fit their lives rather than the other way round. This is something that even Wikipedia, it seems, has been unable to achieve.
* {{cite journal |author=Wang, Yu-Chun; Tsai, Richard Tzong-Han; Hsu, Wen-Lian|title=Web-based pattern learning for named entity translation in Korean-Chinese cross-language information retrieval|publisher=EXPERT SYSTEMS WITH APPLICATIONS|date=0|year=2009|month=MAR|volume=36|issue=2|page=3990|pages=6}}
:Named entity (NE) translation plays an important role in many applications, such as information retrieval and machine translation, In this paper, we focus on translating NEs from Korean to Chinese in order to improve Korean-Chinese cross-language information retrieval (KCIR). The ideographic nature of Chinese makes NE translation difficult because one syllable may map to several Chinese characters. We propose a hybrid NE translation system. First, we integrate two online databases to extend the coverage of our bilingual dictionaries. We use Wikipedia as a translation tool based on the inter-language links between the Korean edition and the Chinese or English editions. We also use Naver.com's people search engine to find a query name's Chinese or English translation. The second component of our system is able to learn Korean-Chinese (K-C), Korean-English (K-E), and English-Chinese (E-C) translation patterns from the web. These patterns can be used to extract K-C, K-E and E-C pairs from Google snippets. We found KCIR performance using this hybrid configuration over five times better than that a dictionary-based configuration using only Naver people search. Mean average precision was as high as 0.3385 and recall reached 0.7578. Our method can handle Chinese, Japanese. Korean. and non-CJK NE translation and improve performance of KCIR substantially. (C) 2008 Elsevier Ltd. All rights reserved.
* {{cite journal |author=Hardy, Christopher R.; Hardy, Nazli W.|title=Simple biodiversity mashups for non-tech-savvy biologists: a demonstration using the liana flora of Pennsylvania, USA|publisher=JOURNAL OF THE TORREY BOTANICAL SOCIETY|date=0|year=2008|month=OCT-DEC|volume=135|issue=4|page=585|pages=10}}
:HARDY, C. R. AND N. W. HARDY (James C. Parks Herbarium, Departments of Biology and Computer Science, Millersville University, Millersville, PA 17551). Simple biodiversity mashups for non-tech-savvy biologists: a demonstration using the liana flora of Pennsylvania, USA. J. Torrey Bot. Soc. 135: 585-594. 2008.-A step-by-step procedure is described and demonstrated using the liana flora of Pennsylvania, USA, for the creation of simple biodiversity informatics applications in the form of Web-mashups. The target audience is non-tech-savvy biologists. For each liana species, the Web-based Liana Atlas of Pennsylvania creates Species Pages by aggregating information or direct links to information on taxonomy, distribution, morphology, genetics, its well as photographs and general encyclopedic or bibliographic information, "live" from third-party websites including the Global Biodiversity Information Facility, the USDA PLANTS database, Wikipedia (R), and GenBank (R). The result is an original, in formation-rich, fully illustrated application providing more up-to-date information on Pennsylvanian lianas in one place than had previously been available elsewhere. More importantly, the procedure described and files available at the demonstration website are portable and customizable to many other biogeographic regions or taxa, and its application requires only basic knowledge of Web navigation and text editors. We hope that this procedure will encourage others, including biologists with limited IT knowledge or at smaller institutions with limited resources, to contribute their own informatics applications valuable to local or regional interest-groups such as educators, students, and amateurs.
* {{cite journal |author=Crouch, Carolyn J.; Crouch, Donald B.; Kamat, Nachiket; Malik, Vikram; Mone, Aditya|title=Dynamic Element Retrieval in the Wikipedia Collection|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=70|pages=10}}
:This paper describes the successful adaptation of our methodology for the dynamic retrieval of XML elements to a semi-structured environment. Working with text that contains both tagged and untagged elements presents particular challenges in this context. Our system is based on the Vector Space Model; basic functions are performed using the Smart experimental retrieval system. Dynamic element retrieval requires only a single indexing of the document collection at the level of the basic indexing node (i.e., the paragraph). It returns a rank-ordered list of elements identical to that produced by the same query against an all-element index of the collection. Experimental results are reported for both the 2006 and 2007 Ad-hoc tasks.
* {{cite journal |author=Lehtonen, Miro; Doucet, Antoine|title=Phrase Detection in the Wikipedia|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=115|pages=7}}
:The Wikipedia XML collection turned out to be rich of marked-up phrases as we carried out our INEX 2007 experiments. Assuming that a phrase occurs at the inline level of the markup, we were able to identify over 18 million phrase occurrences, most of which were either the anchor text of a hyperlink or a passage of text with added emphasis. As our IR system - EXTIRP - indexed the documents, the detected inline-level elements were duplicated in the markup with two direct consequences: 1) The frequency of the phrase terms increased, and 2) the word sequences changed. Because the markup was manipulated before computing word sequences for a phrase index, the actual multi-word phrases became easier to detect. The effect of duplicating the inline-level elements was tested by producing two run submissions in ways that were similar except for the duplication. According to the official INEX 2007 metric, the positive effect of duplicated phrases was clear.
* {{cite journal |author=Kutty, Sangeetha; Tran, Tien; Nayak, Richi; Li, Yuefeng|title=Clustering XML Documents Using Closed Frequent Subtrees: A Structural Similarity Approach|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=183|pages=12}}
:This paper presents the experimental study conducted over the INEX 2007 Document Mining Challenge corpus employing a frequent subtree-based incremental clustering approach. Using the structural information of the XML documents, the closed frequent subtrees are generated. A matrix is then developed representing the closed frequent subtree distribution in documents. This matrix is used to progressively cluster the XML documents. In spite of the large number of documents in INEX 2007 Wikipedia dataset, the proposed frequent subtree-based incremental clustering approach was successful in clustering the documents.
* {{cite journal |author=Tran, Tien; Nayak, Richi; Bruza, Peter|title=Document Clustering Using Incremental and Pairwise Approaches|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=222|pages=12}}
:This paper presents the experiments and results of a clustering approach for clustering of the large Wikipedia dataset in the INEX 2007 Document Mining Challenge. The clustering approach employed makes use of an incremental clustering method and a pairwise clustering method. The approach enables us to perform the clustering task on a large dataset by first reducing the dimension of the dataset to an undefined number of clusters using the incremental method. The lower-dimension dataset is then clustered to a required number of clusters using the pairwise method. In this way, clustering of the large number of documents is performed successfully and the accuracy of the clustering solution is achieved.
* {{cite journal |author=de Vries, Arien P.; Vercoustre, Anne-Marie; Thom, James A.; Craswell, Nick; Lalmas, Mounia|title=Overview of the INEX 2007 Entity Ranking Track|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=245|pages=7}}
:Many realistic user tasks involve the retrieval of specific entities instead of just any type of documents. Examples of information needs include 'Countries where one can pay with the euro' or 'Impressionist art museums in The Netherlands'. The Initiative for Evaluation of XML Retrieval (INEX) started the XML Entity Ranking track (INEX-XER) to create a test collection for entity retrieval in Wikipedia. Entities are assumed to correspond to Wikipedia entries. The goal of the track is to evaluate how well systems can rank entities in response to a query; the set of entities to be ranked is assumed to be loosely defined either by a generic category (entity ranking) or by some example entities (list completion). This track overview introduces the track setup, and discusses the implications of the new relevance notion for entity ranking in comparison to ad hoc retrieval.
* {{cite journal |author=Demartini, Gianluca; Firan, Claudiu S.; Iofciu, Tereza|title=L3S at INEX 2007: Query Expansion for Entity Ranking Using a Highly Accurate Ontology|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=252|pages=12}}
:Entity ranking on Web scale datasets is still an open challenge. Several resources, as for example Wikipedia-based ontologies, can be used to improve the quality of the entity ranking produced by a system. In this paper we focus on the Wikipedia corpus and propose algorithms for finding entities based on query relaxation using category information. The main contribution is a methodology for expanding the user query by exploiting the semantic structure of the dataset. Our approach focuses on constructing queries using not only keywords from the topic, but also information about relevant categories. This is done leveraging on a highly accurate ontology which is matched to the character strings of the topic. The evaluation is performed using the INEX 2007 Wikipedia collection and entity ranking topics. The results show that our approach performs effectively, especially for early precision metrics.
* {{cite journal |author=Jamsen, Janne; Nappila, Turkka; Arvola, Paavo|title=Entity Ranking Based on Category Expansion|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=264|pages=15}}
:This paper introduces category and link expansion strategies for the XML Entity Ranking track at INEX 2007. Category expansion is a coefficient propagation method for the Wikipedia category hierarchy based on given categories or categories derived from sample entities. Link expansion utilizes links between Wikipedia articles. The strategies are evaluated within the entity ranking and list completion tasks.
* {{cite journal |author=Shiozaki, Hitohiro; Eguchi, Koji|title=Entity Ranking from Annotated Text Collections Using Multitype Topic Models|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=279|pages=14}}
:Very recently, topic model-based retrieval methods have produced good results using Latent Dirichlet Allocation (LDA) model or its variants in language modeling framework. However, for the task of retrieving annotated documents when using the LDA-based methods, some post-processing is required outside the model in order to make use of multiple word types that are specified by the annotations. In this paper, we explore new retrieval methods using a 'multitype topic model' that can directly handle multiple word types, such as annotated entities, category labels and other words that are typically used in Wikipedia. We investigate how to effectively apply the multitype topic model to retrieve documents from an annotated collection, and show the effectiveness of our methods through experiments on entity ranking using a Wikipedia collection.
* {{cite journal |author=Murugeshan, Meenakshi Sundaram; Mukherjee, Saswati|title=An n-Gram and Initial Description Based Approach for Entity Ranking Track|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=293|pages=13}}
:The most important work that takes the center stage in the Entity Ranking track of INEX is proper query formation. Both the subtasks, namely Entity Ranking and List Completion, would immensely benefit if the given query can be expanded with more relevant terms, thereby improving the efficiency of the search engine. This paper stresses on the correct identification of "Meaningful n-grams" from the given title and proper selection of the "Prominent n-grams" among them as the utmost important task that improves query formation and hence improves the efficiencies of the overall Entity Ranking tasks. We also exploit the Initial Descriptions (IDES) of the Wikipedia articles for ranking the retrieved answers based on their similarities with the given topic. List completion task is further aided by the related Wikipedia articles that boosted the score of retrieved answers.
* {{cite journal |author=Tsikrika, Theodora; Serdyukov, Pavel; Rode, Henning; Westerveld, Thijs; Aly, Robin; Hiemstra, Djoerd; de Vries, Arjen P.|title=Structured Document Retrieval, Multimedia Retrieval, and Entity Ranking Using PF/Tijah|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=306|pages=15}}
:CWI and University of Twente used PF/Tijah, a flexible XML retrieval system, to evaluate structured document retrieval, multimedia retrieval, and entity ranking tasks in the context of INEX 2007. For the retrieval of textual and multimedia elements in the Wikipedia data, we investigated various length priors and found that biasing towards longer elements than the ones retrieved by our language modelling approach can be useful. For retrieving images in isolation, we found that their associated text is a very good source of evidence in the Wikipedia collection. For the entity ranking task, we used random walks to model multi-step relevance propagation from the articles describing entities to all related entities and further, and obtained promising results.
* {{cite journal |author=Vercoustre, Anne-Marie; Pehcevski, Jovan; Thom, James A.|title=Using Wikipedia Categories and Links in Entity Ranking|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=321|pages=15}}
:This paper describes the participation of the INRIA group in the INEX 2007 XML entity ranking and ad hoc tracks. We developed a system for ranking Wikipedia entities in answer to a query. Our approach utilises the known categories, the link structure of Wikipedia, as well as the link co-occurrences with the examples (when provided) to improve the effectiveness of entity ranking. Our experiments on both the training and the testing data sets demonstrate that the use of categories and the link structure of Wikipedia can significantly improve entity retrieval effectiveness. We also use our system for the ad hoc tasks by inferring target categories from the title of the query. The results were worse than when using a full-text search engine, which confirms our hypothesis that ad hoc retrieval and entity retrieval are two different tasks.
* {{cite journal |author=Toms, Elaine G.; O'Brien, Heather; Mackenzie, Tayze; Jordan, Chris; Freund, Luanne; Toze, Sandra; Dawe, Emilie; MacNutt, Alexandra|title=Task Effects on Interactive Search: The Query Factor|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=359|pages=14}}
:The purpose of this research is to examine how search differs according to selected task variables. Three types of task information goals and two types of task structures were explored. This mixed within- and between-subjects designed study had 96 participants complete three of 12 tasks in a laboratory setting using a specialized search system based on Lucene. Using a combination metrics (user perception collected by questionnaires, transaction log data, and characteristics of relevant documents), we assessed the effect of goals and structure on search as demonstrated through queries and their use in interactive searching.
* {{cite journal |author=Huang, Darren Wei Che; Xu, Yue; Trotman, Andrew; Geva, Shlomo|title=Overview of INEX 2007 Link the Wiki Track|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=373|pages=15}}
:Wikipedia is becoming ever more popular. Linking between documents is typically provided in similar environments in order to achieve collaborative knowledge sharing. However, this functionality in Wikipedia is not integrated into the document creation process and the quality of automatically generated links has never been quantified. The Link the Wiki (LTW) track at INEX in 2007 aimed at producing a standard procedure, metrics and a discussion forum for the evaluation of link discovery. The tasks offered by the LTW track as well as its evaluation present considerable research challenges. This paper briefly described the LTW task and the procedure of evaluation used at LTW track in 2007. Automated link discovery methods used by participants are outlined. An overview of the evaluation results is concisely presented and further experiments are reported.
* {{cite journal |author=Fachry, Khairun Nisa; Kamps, Jaap; Koolen, Marijn; Mang, Junte|title=Using and Detecting Links in Wikipedia|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=388|pages=16}}
:In this paper, we document our efforts at INEX 2007 where we participated in the Ad Hoc Track, the Link the Wiki Track, and the Interactive Track that continued from INEX 2006. Our main aims at INEX 2007 were the following. For the Ad Hoc Track, we investigated the effectiveness of incorporating link evidence into the model, and of a CAS filtering method exploiting the structural hints in the INEX topics. For the Link the Wiki Track, we investigated the relative effectiveness of link detection based on retrieving similar documents with the Vector Space Model, and then filter with the names of Wikipedia articles to establish a link. For the Interactive Track, we took part in the interactive experiment comparing an element retrieval system with a passage retrieval system. The main results are the following. For the Ad Hoc Track, we see that link priors improve most of our runs for the Relevant in Context and Best in Context Tasks, and that CAS pool filtering is effective for the Relevant in Context and Best in Context Tasks. For the Link the Wiki Track, the results show that detecting links with name matching works relatively well, though links were generally under-generated, which hurt the performance. For the Interactive Track, our test-persons showed a weak preference for the element retrieval system over the passage retrieval system.
* {{cite journal |author=Geva, Shlomo|title=GPX: Ad-Hoc Queries and Automated Link Discovery in the Wikipedia|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=404|pages=13}}
:The INEX 2007 evaluation was based on the Wikipedia collection. In this paper we describe some modifications to the GPX search engine and the approach taken in the Ad-hoc and the Link-the-Wiki tracks. In earlier version of GPX scores were recursively propagated from text containing nodes, through ancestors, all the way to the document root of the XML tree. In this paper we describe a simplification whereby the score of each node is computed directly, doing away with the score propagation mechanism. Results indicate slightly improved performance. The GPX search engine was used in the Link-the-Wiki track to identify prospective incoming links to new Wikipedia pages. We also describe a simple and efficient approach to the identification of prospective outgoing links in new Wikipedia pages. We present and discuss evaluation results.
* {{cite journal |author=Jenkinson, Dylan; Trotman, Andrew|title=Wikipedia Ad Hoc Passage Retrieval and Wikipedia Document Linking|publisher=FOCUSED ACCESS TO XML DOCUMENTS|date=DEC 17-19, 2007|year=2008|month=0|volume=4862|issue=0|page=426|pages=14}}
:Ad hoc passage retrieval within the Wikipedia is examined in the context of INEX 2007. An analysis of the INEX 2006 assessments suggests that fixed sized window of about 300 terms is consistently seen and that this might be a good retrieval strategy. In runs submitted to INEX, potentially relevant documents were identified using BM25 (trained on INEX 2006 data). For each potentially relevant document the location of every search term was identified and the center (mean) located. A fixed sized window was then centered on this location. A method of removing outliers was examined in which all terms occurring outside one standard deviation of the center were considered outliers and the center recomputed without them. Both techniques were examined with and without stemming. For Wikipedia linking we identified terms within the document that were over-represented and from the top few generated queries of different lengths. A BM25 ranking search engine was used to identify potentially relevant documents. Links from the source document to the potentially relevant documents (and back) were constructed (at a granularity of whole document). The best performing run used the 4 most over-represented search terms to retrieve 200 documents, and the next 4 to retrieve 50 more.
* {{cite journal |author=Li, Yun; Huang, Kaiyan; Ren, Fuji; Zhong, Yixin|title=SEARCHING AND COMPUTING FOR VOCABULARIES WITH SEMANTIC CORRELATIONS FROM CHINESE WIKIPEDIA|publisher=CIICT 2008: PROCEEDINGS OF CHINA-IRELAND INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATIONS TECHNOLOGIES 2008|date=SEP 26-28, 2008|year=2008|month=0|volume=0|issue=0|page=58|pages=6}}
:This paper introduces experiment on searching for semantically correlated vocabularies in Chinese Wikipedia pages and computing semantic correlations. Based on the 54,745 structured documents generated from Wikipedia pages, we explore about 400,000 pairs of Wikipedia vocabularies considering of hyperlinks, overlapped text and document positions. Semantic relatedness is calculated based on the relatedness of Wikipedia documents. From comparing experiment we analyze the reliability of our measures and some other properties.
* {{cite journal |author=Curino, Carlo A.; Moon, Hyun J.; Zaniolo, Carlo|title=Managing the History of Metadata in Support for DB Archiving and Schema Evolution|publisher=ADVANCES IN CONCEPTUAL MODELING - CHALLENGES AND OPPORTUNITIES|date=OCT 20-23, 2008|year=2008|month=0|volume=5232|issue=0|page=78|pages=11}}
:Modern information systems, and web information systems in particular, are faced with frequent database schema changes, which generate the necessity to manage them and preserve the schema, evolution history. In this paper, we describe the Panta Rhei Framework designed to provide powerful tools that: (i) facilitate schema, evolution and guide the Database Administrator in planning and evaluating changes; (ii) support. automatic rewriting of legacy queries against the current schema version, (iii) enable efficient archiving of the histories of data and metadata, and (iv) support complex temporal queries over such histories. We then introduce the Historical Metadata, Manager (HMM), a tool designed to facilitate the process of documenting and querying the schema evolution itself. We use the schema history of the Wikipedia database as a telling example of the many uses and benefits of HMM.
* {{cite journal |author=Daub, Jennifer; Gardner, Paul P.; Tate, John; Ramskold, Daniel; Manske, Magnus; Scott, William G.; Weinberg, Zasha; Griffiths-Jones, Sam; Bateman, Alex|title=The RNA WikiProject: Community annotation of RNA families|publisher=RNA-A PUBLICATION OF THE RNA SOCIETY|date=0|year=2008|month=DEC|volume=14|issue=12|page=2462|pages=3}}
:The online encyclopedia Wikipedia has become one of the most important online references in the world and has a substantial and growing scientific content. A search of Google with many RNA-related keywords identifies a Wikipedia article as the top hit. We believe that the RNA community has an important and timely opportunity to maximize the content and quality of RNA information in Wikipedia. To this end, we have formed the RNA WikiProject (http://en.wikipedia.org/wiki/Wikipedia: WikiProject_RNA) as part of the larger Molecular and Cellular Biology WikiProject. We have created over 600 new Wikipedia articles describing families of noncoding RNAs based on the Rfam database, and invite the community to update, edit, and correct these articles. The Rfam database now redistributes this Wikipedia content as the primary textual annotation of its RNA families. Users can, therefore, for the first time, directly edit the content of one of the major RNA databases. We believe that this Wikipedia/Rfam link acts as a functioning model for incorporating community annotation into molecular biology databases.
* {{cite journal |author=Poudat, Celine; Loiseau, Sylvain|title=Representation and lexical characterization of sciences in Wikipedia|publisher=REVUE FRANCAISE DE LINGUISTIQUE APPLIQUEE|date=0|year=2007|month=DEC|volume=12|issue=2|page=29|pages=16}}
:The free and online encyclopaedia project Wikipedia has become in less than six years one of the most prominent commons-based peer production example. The way the project works and evolves is now at stake for academics eager to explore auto-organized structures. Although many studies have been led on the connections between contributors, the linguistic properties of Wikipedia productions remain almost unexplored. In this article, we focus on the way sciences are represented within the project and examine the general and epistemic lexical characteristics of the articles thanks to the comparison of a set of corpora extracted from Wikipedia's category system.
* {{cite journal |author=Amichai-Hamburger, Yair; Lamdan, Naama; Madiel, Rinat; Hayat, Tsahi|title=Personality Characteristics of Wikipedia Members|publisher=CYBERPSYCHOLOGY & BEHAVIOR|date=0|year=2008|month=DEC|volume=11|issue=6|page=679|pages=3}}
:Wikipedia is an online, free access, volunteer-contributed encyclopedia. This article focuses on the Wikipedians' (Wikipedia users) personality characteristics, studying Wikipedians' conceptions of Real-Me and BFI dimensions. To survey these aspects, we posted links to two online web questionnaires; one was targeted at Wikipedians and the second to non-Wikipedia users. One hundred and thirty-nine subjects participated in the study, of which 69 were active Wikipedia members. It was found that Wikipedia members locate their real me on the Internet more frequently as compared to non-Wikipedia members. Variance analysis revealed significant differences between Wikipedia members and non-Wikipedia members in agreeableness, openness, and conscientiousness, which were lower for the Wikipedia members. An interaction was found between Wikipedia membership and gender: introverted women were more likely to be Wikipedia members as compared with extroverted women. The results of this study are discussed with special emphasis on the understanding of the motivators of Wikipedia members.
* {{cite journal |author=Huang, Jin-Xia; Ryu, Pum-Mo; Choi, Key-Sun|title=An Empirical Research on Extracting Relations from Wikipedia Text|publisher=INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2008|date=NOV 02-05, 2008|year=2008|month=0|volume=5326|issue=0|page=241|pages=9}}
:A feature based relation classification approach is presented, in which probabilistic and semantic relatedness features between patterns and relation types are employed with other linguistic information. The importance of each feature set is evaluated with Chi-square estimator, and the experiments show that, the relatedness features have big impact on the relation classification performance. A series experiments are also performed to evaluate the different machine learning approaches on relation classification. among which Bayesian Outperformed other approaches including Support Vector Machine (SVM).
* {{cite journal |author=Clauson, Kevin A.; Polen, Hyla H.; Boulos, Maged N. Kamel; Dzenowagis, Joan H.|title=Scope, Completeness, and Accuracy of Drug Information in Wikipedia|publisher=ANNALS OF PHARMACOTHERAPY|date=NOV 08-12, 2008|year=2008|month=DEC|volume=42|issue=12|page=1814|pages=8}}
:With the advent of Web 2.0 technologies, user-edited online resources such as Wikipedia are increasingly tapped for information. However, there is little research on the quality of healthy information found in Wikipedia. OBJECTIVE: To compare the scope, completeness, and accuracy of drug information in Wikipedia with that of a free, online, traditionally edited database (Medscape Drug Reference [MDR]). METHODS: Wikipedia and MDR were assessed on 8 categories of drug information. Questions were constructed and answers were verified with authoritative resources . Wikipedia and MDR were evaluated according to scope (breadth of coverage) and completeness. Accuracy was tracked by factual errors and errors of omission. Descriptive statistics were used to summarize the components. Fisher's exact test was used to compare scope and paired Student's t-test was used to compare current results in Wikipedia with entries 90 days prior to the current access. RESULTS: Wikipedia was able to answer significantly fewer drug information questions (40.0%) compared with MDR (82.5%; P < 0.001). Wikipedia performed poorly regarding information on dosing, with a score of 0% versus the MDR score of 90.0%. Answers found in Wikipedia were 76.0% complete, while MDR provided answers that were 95.5% complete; overall, Wikipedia answers were less complete than those in Medscape (p<0.001). No factual errors were found in Wikipedia, whereas 4 answers in Medscape conflicted with the answer key; errors of omission were higher in Wikipedia (n = 48) than in MDR (n = 14). There was a marked improvement in Wikipedia over time, as current entries were superior to those 90 days prior (p=0.024). CONCLUSIONS: Wikipedia has a more narrow scope, is less complete, and has more errors of omission than the comparator database. Wikipedia may be useful point of engagement for consumers, but is not authoritative and should only be a supplemental source of drug information.
* {{cite journal |author=Rejas-Muslera, Ricardo J.; Cuadrado, Juan J.; Abran, Alain; Sicilia, Miguel A.|title=Information Economy Philosophy in Universal Education. The Open Educational Resources (OER): Technical, Socioeconomics and Legal Aspects|publisher=2008 IEEE INTERNATIONAL PROFESSIONAL COMMUNICATION CONFERENCE|date=JUL 13-16, 2008|year=2008|month=0|volume=0|issue=0|page=301|pages=5}}
:According to Dr. B.R. Ambedkar's definition [1], Open Educational Resources (0 ER) are based on the philosophical view of knowledge as a collective, social product. In consequence, it is also desirable to make it a social property. Terry Foote, one of the Wikipedia project's chairperson emphasize this: "Imagine a world in which every single person is given free access to the sum of all human knowledge" [2]. The importance of open educational resources (OERs) has been widely documented and demonstrated and a high magnitude impact is to be expected for OERs in the near future. This paper presents on overview of OERs and its current usage. Then, the paper goes into detailed some related aspects. Which is the impact, in socio-economic terms, of OER, especially for the less developed? Which legal aspects influence the diffusion and use of OER? And, which are the technical resources needed for them?.
* {{cite journal |author=Shieh, Jyh-Ren; Yeh, Yang-Ting; Lin, Chih-Hung; Lin, Ching-Yung; Wu, Ja-Ling|title=USING SEMANTIC GRAPHS FOR IMAGE SEARCH|publisher=2008  IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-4|date=JUN 23-26, 2008|year=2008|month=0|volume=0|issue=0|page=105|pages=4}}
:In this paper, we propose a Semantic Graphs for Image Search (SGIS) system, which provides a novel way for image search by utilizing collaborative knowledge in Wikipedia and network analysis to form semantic graphs for search-term suggestion. The collaborative article editing process of Wikipedia's contributors is formalized as bipartite graphs that are folded into networks between terms. When user types in a search term, SGIS automatically retrieves an interactive semantic graph of related terms that allow users easily find related images not limited to a specific search term. Interactive semantic graph then serves as an interface to retrieve images through existing commercial search engines. This method significantly saves users' time by avoiding multiple search keywords that are usually required in generic search engines. It benefits both naive user who does not possess a large vocabulary (e.g., students) and professionals who look for images on a regular basis. In our experiments, 85% of the participants favored SGIS system than commercial search engines.
* {{cite journal |author=Zhou, Aoying; Zhang, Rong; Qian, Weining; Vu, Quang Hieu; Hu, Tianming|title=Adaptive indexing for content-based search in P2P systems|publisher=DATA & KNOWLEDGE ENGINEERING|date=0|year=2008|month=DEC|volume=67|issue=3|page=381|pages=18}}
:One of the major challenges in Peer-to-Peer (P2P) file sharing systems is to support content-based search. Although there have been some proposals to address this challenge, they share the same weakness of using either servers or super-peers to keep global knowledge, which is required to identify importance of terms to avoid popular terms in query processing. As a result, they are not scalable and are prone to the bottleneck problem, which is caused by the high visiting load at the global knowledge maintainers. To that end, in this paper, we propose a novel adaptive indexing approach for content-based search in P2P systems, which can identify importance of terms without keeping global knowledge. Our method is based on an adaptive indexing structure that combines a Chord ring and a balanced tree. The tree is used to aggregate and classify terms adaptively, while the Chord ring is used to index terms of nodes in the tree. Specifically, at each node of the tree, the system classifies terms as either important or unimportant. Important terms, which can distinguish the node from its neighbor nodes, are indexed in the Chord ring. On the other hand, unimportant terms, which are either popular or rare terms, are aggregated to higher level nodes. Such classification enables the system to process queries on the fly without the need for global knowledge. Besides, compared to the methods that index terms separately, term aggregation reduces the indexing cost significantly. Taking advantage of the tree structure, we also develop an efficient search algorithm to tackle the bottleneck problem near the root. Finally, our extensive experiments on both benchmark and Wikipedia datasets validated the effectiveness and efficiency of the proposed method. (c) 2008 Published by Elsevier B.V.
* {{cite journal |author=Sumpter, David J. T.; Krause, Jens; James, Richard; Couzin, Iain D.; Ward, Ashley J. W.|title=Consensus Decision Making by Fish|publisher=CURRENT BIOLOGY|date=0|year=2008|month=44500|volume=18|issue=22|page=1773|pages=5}}
:Decisions reached through consensus are often more accurate, because they efficiently utilize the diverse information possessed by group members [1-3]. A trust in consensus decision making underlies many of our democratic political and judicial institutions [4], as well as the design of web tools such as Google, Wikipedia, and prediction markets [5, 6]. In theory, consensus for the option favored by the majority of group members will lead to improved decision-making accuracy as group size increases [2, 4]. Although group-living animals are known to utilize social information [7-10], little is known about whether or not decision accuracy increases with group size. In order to reach consensus, group members must be able to integrate the disparate information they possess. Positive feedback, resulting from copying others, can spread information quickly through the group, but it can also result in all individuals making the same, possibly incorrect, choice [8,11,12]. On the other hand, if individuals never copy each other, their decision making remains independent and they fail to benefit from information exchange [4]. Here, we show how small groups of sticklebacks (Gasterosteus aculeatus) reach consensus when choosing which of two replica fish to follow. As group size increases, the fish make more accurate decisions, becoming better at discriminating subtle phenotypic differences of the replicas. A simple quorum rule proves sufficient to explain our observations, suggesting that animals can make accurate decisions without the need for complicated comparison of the information they possess. Furthermore, although submission to peers can lead to occasional cascades of incorrect decisions, these can be explained as a byproduct of what is usually accurate consensus decision making.
* {{cite journal |author=Stillman-Lowe, C.|title=WIKIPEDIA COMES SECOND|publisher=BRITISH DENTAL JOURNAL|date=0|year=2008|month=NOV|volume=205|issue=10|page=525|pages=1}}
:0
* {{cite journal |author=Ahmadi, Navid; Repenning, Alexander; Ioannidou, Andri|title=Collaborative End-User Development on Handheld Devices|publisher=2008 IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING, PROCEEDINGS|date=SEP 15-19, 2008|year=2008|month=0|volume=0|issue=0|page=237|pages=5}}
:Web 2.0 has enabled end users to collaborate through their own developed artifacts, moving on from text (e.g., Wikipedia, Blogs) to images (e.g., Flickr) and movies (e.g., YouTube), changing end-user's role from consumer to producer. But still there is no support for collaboration through interactive end-user developed artifacts, especially for emerging handheld devices, which are the next collaborative platform. Featuring fast always-on networks, Web browsers that are as powerful as their desktop counterparts, and innovative user interfaces, the newest generation of handheld devices can run highly interactive content as Web applications. We have created Ristretto (Mobile), a Web-compliant framework for running end-user developed applications on handheld devices. The Web-based Ristretto Mobile includes compiler and runtime components to turn end-user applications into Web applications that can run on compatible handheld devices, including the Apple iPhone and Nokia N800. Our paper reports on the technological and cognitive challenges in creating interactive content that runs efficiently and is user accessible on handheld devices.
* {{cite journal |author=Dalli, Daniele; Corciolani, Matteo|title=Collective forms of resistance: the transformative power of moderate communities Evidence from the BookCrossing case|publisher=INTERNATIONAL JOURNAL OF MARKET RESEARCH|date=0|year=2008|month=0|volume=50|issue=6|page=757|pages=19}}
:This paper deals with collective consumer resistance - that is, organised forms of reaction against the market. In detail, the paper describes BookCrossing (BC) as an alternative mode of book exchange. This is a moderate form of resistance: BC members do not pursue radical, extremist or extreme forms of reaction. Moreover, they act in an alternative way (gift-giving) compared to the traditional market exchange system. They criticise the market system and their activity presents some interesting 'transformative' properties. Not so paradoxically, these forms of moderate resistance in some way support the market in order to meet new needs: solidarity, democracy, consumers' emancipation. Many contemporary communities (e.g. Wayn, Wikipedia, Couchsurfing) seem to possess traits in common with BookCrossing. It is certain that they are not aimed at market subversion: they are aimed at using the market in a different way, in order to compensate for some of its drawbacks. Taken together, these communities collect millions of people around the world, and their role in the emancipation of the consumer society is growing rapidly.
* {{cite journal |author=Nov, Oded; Kuk, George|title=Open source content contributors' response to free-riding: The effect of personality and context|publisher=COMPUTERS IN HUMAN BEHAVIOR|date=0|year=2008|month=SEP|volume=24|issue=6|page=2848|pages=14}}
:We address concerns about the sustainability of the open Source content model by examining the effect of external appropriation, whereby the product of open source contributors' efforts is monetized by a party that did not contribute to the project, on intended effort withdrawal (reduction in contribution level). We examine both the personality of contributors and their contextual motivations to contribute, using a scenario-based survey of Wikipedia contributors. The findings Suggest that perceived justice of the open source license terms, and intrinsic motivations are both negatively related with effort withdrawal intentions. Moreover, we find that the effect of the fairness personality trait on effort withdrawal is stronger for individuals who are low in perceived justice and weaker for individuals high in justice. The findings of factors predicting effort withdrawal contribute to the open source literature, which tends to focus on contribution and motivations, but not on what impacts changes in individual contribution levels. (C) 2008 Elsevier Ltd. All rights reserved.
* {{cite journal |author=Li, Yun; Huang, Kaiyan; Tsuchiya, Seiji; Ren, Fuji; Zhong, Yixin|title=Exploring Words with Semantic Correlations from Chinese Wikipedia|publisher=INTELLIGENT INFORMATION PROCESSING IV|date=OCT 19-22, 2008|year=2008|month=0|volume=0|issue=0|page=103|pages=6}}
:In this paper, we work on semantic correlation between Chinese words based on Wikipedia documents. A corpus with about 50,000 structured documents is generated from Wikipedia pages. Then considering of hyper-links, text overlaps and word frequency, about 300,000 word pairs with semantic correlations are explored from these documents. We roughly measure the degree of semantic correlations and find groups with tight semantic correlations by self clustering.
* {{cite journal |author=Pinkwart, Niels|title=Applying Web 2.0 Design Principles in the Design of Cooperative Applications|publisher=COOPERATIVE DESIGN, VISUALIZATION, AND ENGINEERING, PROCEEDINGS|date=SEP 21-25, 2008|year=2008|month=0|volume=5220|issue=0|page=229|pages=8}}
:Web 2.0 is a term frequently mentioned in media - apparently, applications such as Wikipedia, Social Network Services, Online Shops with integrated recommender systems, or Sharing Services like flickr, all of which rely on user's activities, contributions, and interactions as a central factor, are fascinating for the general public. This leads to a success of these systems that seemingly exceeds the impact of most "traditional" groupware applications that have emerged from CSCW research. This paper discusses differences and similarities between novel Web 2.0 tools and more traditional CSCW application in terms of technologies, system design and success factors. Based on this analysis, the design of the cooperative learning application LARGO is presented to illustrate how Web 2.0 success factors can be considered for the design of cooperative environments.
* {{cite journal |author=Schoenhofen, Peter; Benczur, Andras; Biro, Istvan; Csalogany, Karoly|title=Cross-Language Retrieval with Wikipedia|publisher=ADVANCES IN MULTILINGUAL AND MULTIMODAL INFORMATION RETRIEVAL|date=SEP 19-21, 2007|year=2008|month=0|volume=5152|issue=0|page=72|pages=8}}
:We demonstrate a twofold use of Wikipedia for cross-lingual information retrieval. As our main contribution, we exploit Wikipedia hyperlinkage for query term disambiguation. We also use bilingual Wikipedia articles for dictionary extension. Our method is based on translation disambiguation; we combine the Wikipedia based technique with a method based on bigram statistics of pairs formed by translations of different source language terms.
* {{cite journal |author=Gonzalez-Cristobal, Jose-Carlos; Goni-Menoyo, Jose Miguel; Villena-Roman, Julio; Lana-Serrano, Sara|title=MIRACLE Progress in Monolingual Information Retrieval at Ad-Hoc CLEF 2007|publisher=ADVANCES IN MULTILINGUAL AND MULTIMODAL INFORMATION RETRIEVAL|date=SEP 19-21, 2007|year=2008|month=0|volume=5152|issue=0|page=156|pages=4}}
:This paper presents the 2007 MIRACLE's team approach to the AdHoc Information Retrieval track. The main work carried out for this campaign has been around monolingual experiments, in the standard and in the robust tracks. The most important contributions have been the general introduction of automatic named-entities extraction and the use of wikipedia resources. For the 2007 campaign, runs were submitted for the following languages and tracks: a) Monolingual: Bulgarian, Hungarian, and Czech. b) Robust monolingual: French, English and Portuguese.
* {{cite journal |author=Giampiccolo, Danilo; Forner, Pamela; Herrera, Jesus; Penas, Anselmo; Ayache, Christelle; Forascu, Corina; Jijkoun, Valentin; Osenova, Petya; Rocha, Paulo; Sacaleanu, Bogdan; Sutcliffe, Richard|title=Overview of the CLEF 2007 Multilingual Question Answering Track|publisher=ADVANCES IN MULTILINGUAL AND MULTIMODAL INFORMATION RETRIEVAL|date=SEP 19-21, 2007|year=2008|month=0|volume=5152|issue=0|page=200|pages=37}}
:The fifth QA campaign at CLEF [1], having its first edition in 2003, offered not only a main task but an Answer Validation Exercise (AVE) [2], which continued last year's pilot, and a new pilot: the Question Answering on Speech Transcripts (QAST) [3, 15]. The main task was characterized by the focus on cross-linguality, while covering as many European languages as possible. As novelty, some QA pairs were grouped in clusters. Every cluster was characterized by a topic (not given to participants). The questions from a cluster possibly contain co-references between one of them and the others. Finally, the need for searching answers in web formats was satisfied by introducing Wikipedia(1) as document corpus. The results and the analyses reported by the participants suggest that the introduction of Wikipedia and the topic related questions led to a drop in systems' performance.

==2009==
===Biblioteche oggi, gennaio-febbraio 2009===
 Biblioteche oggi, gennaio-febbraio 2009, pp. 15-22, Nuove tendenze: ''[http://www.bibliotecheoggi.it/content/20090101501.pdf Spiacenti, la conoscenza enciclopedica si è trasferita online]
:Wikipedia e le altre: un fenomeno in rapida espansione destinato a determinare cambiamenti di portata epocale'', di Fabio Metitieri (una fonte citabile).

===[http://www.eupjournals.com/toc/epi/6/1?cookieSet=1# Episteme, feb. 2009]===

* "Introduction: The Epistemology of Mass Collaboration", Don Fallis
* "WIKIPEDIA and the Epistemology of Testimony", Deborah Perron Tollefsen
* "Web 2.0 vs. the Semantic Web: A Philosophical Assessment", Luciano Floridi
* "The Epistemic Cultures of Science and WIKIPEDIA: A Comparison", K. Brad Wray
* "The Fate of Expertise after WIKIPEDIA", Lawrence M. Sanger
* "On Trusting WIKIPEDIA", P. D. Magnus
* "Prediction Markets: The Practical and Normative Possibilities for the Social Production of Knowledge", George Bragues